/Dry-Beans-Classification-Competition

It's simple. You are given a set of features extracted from the shape of the beans in images and it's required to predict the type of each bean. There are 7 bean types in this dataset. Getting started You can check this notebook from the last years competition. What's expected? We encourage you to do the following. Form a team Load and manipulate the data Publish notebooks with your insights Open a Discussion with your questions and/or findings. Train one or more classifier Submit the results and see the score on the leaderboard Compare the performance of your different models Acknowledgement The dataset provided in this competition is obtained from UC Irvine Machine Learning Repository - Dry Bean Dataset. This competition is for educational purposes only.

Primary LanguageJupyter Notebook

Dry-Beans-Classification-Competition

It's simple. You are given a set of features extracted from the shape of the beans in images and it's required to predict the type of each bean. There are 7 bean types in this dataset.

What's expected?

  • We form a team:

  • Load and manipulate the data.

  • Publish notebooks with our insights.

  • Open a Discussion with many questions and/or findings.

  • Train one or more classifier.

  • Submit the results and see the score on the leaderboard.

  • Compare the performance of our different models.

Acknowledgement

The dataset provided in this competition is obtained from UC Irvine Machine Learning Repository - Dry Bean Dataset. This competition is for educational purposes only.

Evaluation

Screenshot 2022-07-14 102310

Rules

This competitions is part of the ITI's AI-Pro training program. In order to have your submission considered in the final evaluation you must follow these rules.

  • All submissions must be made through notebooks that show ALL the steps taken in order to generate this submission.

  • You are NOT allowed to upload processed data to your submission notebook. For example, you CANNOT prepare the data using Orange and upload the prepared data for the model to be directly trained on. All the data preparation steps must be in the notebook. However, you can use any tool, e.g., Orange, to learn more about the data and/or make decisions BUT YOU'LL NEED TO WRITE YOUR FINAL DECISIONS IN PYTHON IN THE SUBMISSION NOTEBOOK.

  • Using External Data is NOT allowed. This means you CANNOT use any data other than the provided data.

  • Discussions with other teams are allowed ONLY through the Discussion Tab in the competitions.

  • It's required that you make your notebook public AFTER the end date of the competition. This allows the organizers to validate the work done and make sure that the order of the participants in the leaderboard reflects the work done by the team. The final leaderboard will be published after organizers review of the submissions' notebooks.

Result

Me and my team Power Rangers won the fourth place in this competation with 93.4% accuracy.

Check the final ranking of the teams

Screenshot 2022-07-14 103021